Orchestrate structured software development workflows: plan with work items and architecture decisions, implement with multi-agent analysis, review with quality lenses, and manage projects via Jira/Linear integration.
Analyses a focused set of screens in a running web application via the Playwright executor. Captures detailed state, screenshots, and computed values. Call browser-analyser when you need to extract HOW a screen behaves, not to enumerate WHERE things are.
Locates routes, screens, and DOM-level component presence in a running web application via the Playwright executor. Call browser-locator when you need to enumerate WHERE things appear in the rendered UI, not to extract their detail.
Analyses codebase implementation details. Call the codebase-analyser agent when you need to find detailed information about specific components. As always, the more detailed your request prompt, the better! :)
Locates files, directories, and components relevant to a feature or task. Call `codebase-locator` with human language prompt describing what you're looking for. Basically a "Super Grep/Glob/LS tool" — Use it if you find yourself desiring to use one of these tools more than once.
codebase-pattern-finder is a useful subagent_type for finding similar implementations, usage examples, or existing patterns that can be modeled after. It will give you concrete code examples based on what you're looking for! It's sorta like codebase-locator, but it will not only tell you the location of files, it will also give you code details!
Resolves the absolute path of the Playwright executor (run.sh) for browser agents. Preloaded by agent definitions that need to invoke the executor without self-discovery; not intended for direct user invocation.
View, create, or edit Accelerator plugin configuration. Manage document templates.
Prepare a repository with the directories and gitignore entries that Accelerator skills expect. Safe to run repeatedly.
Apply pending Accelerator meta-directory migrations to bring a repo into line with the latest plugin schema. Destructive by default but guarded — refuses to run on a dirty working tree and prints a one-line preview per pending migration before applying.
Resolves all configured document-discovery paths for the current project. Preloaded by agent definitions that need config-driven directory locations; not intended for direct user invocation.
Executes bash commands
Hook triggers when Bash tool is used
Uses power tools
Uses Bash, Write, or Edit tools
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A Claude Code plugin for structured, context-efficient software development.
Add the marketplace and install the stable plugin:
/plugin marketplace add atomicinnovation/accelerator
/plugin install accelerator@atomic-innovation
Then initialise your project and run the research → plan → implement loop:
/accelerator:init
/accelerator:research-codebase "how does auth work?" # 1. research
/accelerator:create-plan # 2. plan (optionally pass a work-item key)
/accelerator:implement-plan # 3. implement
See the Development Loop for the full workflow, and Installation for the prerelease channel (where the newest features land first), local checkout, and compatibility details.
Accelerator structures development into discrete phases — research, plan, implement — where each phase runs with minimal context and communicates with the next through the filesystem. This design is intentional: by writing research findings, plans, and other artifacts to disk rather than holding them in the conversation, each step stays focused and avoids the quality degradation that comes with large, cluttered context windows.
The result is a development workflow where:
meta/ directory) serves as persistent
shared memory between phases and sessionsFor example, a research phase might read 50 files across a codebase, but only a structured summary is written to disk and passed to the planning phase — keeping the planner focused and accurate.
The primary workflow is a three-phase loop:
research-codebase → create-plan → implement-plan
↓ ↓ ↓
meta/research/codebase/ meta/plans/ checked-off plan
Research (/accelerator:research-codebase "how does auth work?"):
Investigate the codebase using parallel subagents. Produces a structured
research document in meta/research/codebase/ with findings, file
references, and architectural context.
Plan (/accelerator:create-plan ENG-1234): Build a phased
implementation plan informed by research. Produces a plan document in
meta/plans/ with specific file changes, success criteria, and testing
strategy. The plan is reviewed by the developer before proceeding.
Implement (/accelerator:implement-plan @meta/plans/plan.md): Execute
the plan phase by phase, checking off success criteria as each phase
completes. The plan file serves as both instructions and progress tracker.
Companion skills handle issue investigation and quick note capture:
/accelerator:research-issue "auth timeout on token refresh" — Investigate
production issues through hypothesis-driven debugging. Accepts stacktraces,
logs, or behavioral descriptions and produces an RCA document in
meta/research/issues/./accelerator:create-note "rate limiter resets on deploy" — Capture a
short-form note (observation, insight, snippet) to meta/notes/.Three complementary skills support this loop:
/accelerator:review-plan @meta/plans/plan.md — Review a plan through
multiple quality lenses before implementation/accelerator:stress-test-plan @meta/plans/plan.md — Interactively
stress-test a plan through adversarial questioning to find issues,
inconsistencies, and gaps/accelerator:validate-plan @meta/plans/plan.md — Verify after
implementation that the code matches the planmeta/ DirectoryEvery project using Accelerator gets a meta/ directory (by default) that
serves as persistent state for the development workflow. Each skill reads from
and writes to predictable paths within it. Run /accelerator:init to
create all directories up front, or let skills create them on first use.
These paths can be overridden via the paths configuration section:
npx claudepluginhub atomicinnovation/accelerator --plugin acceleratorNo description provided.
Implementation planning, execution, and PR creation workflows with multi-agent collaboration
For easy problems, start here. For harder problems, do this after Explore.
Complete task implementation workflow - accepts plan documents, issues, or task descriptions
AI-Driven Engineering workflow commands for managing issues, tasks, implementation, and PRs.
Feature development with code-architect/explorer/reviewer agents, CLAUDE.md audit and session learnings, and Agent Skills creation with eval benchmarking from Anthropic.